扩展的数据帧具有在原始行

我有一个数据帧作为多的行，两列的范围如下：扩展的数据帧具有在原始行

structure(list(symbol = c("u", "n", "v", "i", "a"), start = c(9L, 
6L, 10L, 8L, 7L), end = c(14L, 15L, 12L, 13L, 11L)), .Names = c("symbol", 
"start", "end"), class = "data.frame", row.names = c("1", "2", 
"3", "4", "5"))

我希望尽可能多的行，也有在的范围内的值（开始，结束）每个符号。所以，最后的数据帧的样子：

structure(list(symbol = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 
4L, 4L, 5L, 5L, 5L, 5L, 5L), .Label = c("a", "l", "n", "v", "y" 
), class = "factor"), value = c(7L, 8L, 9L, 10L, 11L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 13L, 14L, 8L, 9L, 10L, 11L, 12L, 10L, 
11L, 12L, 13L, 14L, 15L, 9L, 10L, 11L, 12L, 13L)), class = "data.frame", row.names = c(NA, 
-30L), .Names = c("symbol", "value"))

我想我可以简单地每行值的列表，然后使用tidyr包的unnest如下：

df$value <- apply(df, 1, function(x) as.list(x[2]:x[3])) 
dput(df) 
structure(list(symbol = structure(c(4L, 3L, 5L, 2L, 1L), .Label = c("a", 
"i", "n", "u", "v"), class = "factor"), start = c(9L, 6L, 10L, 
8L, 7L), end = c(14L, 15L, 12L, 13L, 11L), value = structure(list(
    `1` = list(9L, 10L, 11L, 12L, 13L, 14L), `2` = list(6L, 7L, 
     8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L), `3` = list(10L, 
     11L, 12L), `4` = list(8L, 9L, 10L, 11L, 12L, 13L), `5` = list(
     7L, 8L, 9L, 10L, 11L)), .Names = c("1", "2", "3", "4", 
"5"))), .Names = c("symbol", "start", "end", "value"), row.names = c("1", 
"2", "3", "4", "5"), class = "data.frame") 

df 
    symbol start end        value 
1  u  9 14    9, 10, 11, 12, 13, 14 
2  n  6 15 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 
3  v 10 12       10, 11, 12 
4  i  8 13    8, 9, 10, 11, 12, 13 
5  a  7 11     7, 8, 9, 10, 11

然后做：

library(tidyr) 
unnest(df, value)

不过，我觉得我打这个悬而未决的特性/错误： https://github.com/tidyverse/tidyr/issues/278

Error: Each column must either be a list of vectors or a list of data frames [value]

有没有更好的方法来做到这一点，特别是避免申请家庭？

来源

2017-10-20 Gopala

赋值给每个一行dplyr，我们可以使用rowwise与do

library(dplyr) 
df1 %>% 
    rowwise() %>% 
    do(data.frame(symbol= .$symbol, value = .$start:.$end)) %>% 
    arrange(symbol) 
# A tibble: 30 x 2 
# symbol value 
# <chr> <int> 
# 1  a  7 
# 2  a  8 
# 3  a  9 
# 4  a 10 
# 5  a 11 
# 6  i  8 
# 7  i  9 
# 8  i 10 
# 9  i 11 
#10  i 12 
# ... with 20 more rows

来源

2017-10-20 02:35:49 akrun

织补简单，呵呵！我只是一直忘记'做'具有多大的力量。试图玩一点这个问题，但只是不能提出正确的步骤。完善。谢谢！ – Gopala

你可以使用data.table和所需的行数（基于start和end每个symbol）复制df，再经过

library(data.table) 

setDT(df) 
df[rep(1:.N, (end - start + 1))][, value := (start - 1) + (1:.N), by = symbol][] 

# symbol start end value 
# 1:  u  9 14  9 
# 2:  u  9 14 10 
# 3:  u  9 14 11 
# 4:  u  9 14 12 
# 5:  u  9 14 13 
# ... etc

来源

2017-10-20 02:26:31 SymbolixAU

也许你可以使用map2来添加一个我们可以从unnest到所需的结果列。

library(tidyverse) 
df %>% 
    mutate(value = map2(start, end, ~ seq(from = .x, to = .y))) %>% 
    select(symbol, value) %>% 
    unnest() 
#> symbol value 
#> 1  u  9 
#> 2  u  10 
#> 3  u  11 
#> 4  u  12 
#> 5  u  13 
#> 6  u  14 
#> 7  n  6 
#> 8  n  7 
#> 9  n  8 
#> 10  n  9 
#> ...etc

来源

2017-10-20 02:44:06 markdly

扩展的数据帧具有在原始行

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